As science and technology advance, we have increasingly higher demand on the quality of life, so that various products facilitating our life are developed and introduced constantly. Wherein, the demand for service robots increases year by year and the service robots can help us working in difficult environments, act as a robot for healthcare and medical treatment, or a mobile household robot for recreation and family affairs service. Human identification technology is the key technology of the service robot. On the other hand, the human identification technology is also used extensively in security systems.
However, the conventional human identification system still has many drawbacks remained to be overcome. For example, a human identification system as disclosed in U.S. Pat. No. 6,567,775 uses all images and sounds in a video for face recognition and speaker recognition and finally performs a fusion calculation. Although this method adopts both face recognition and speaker recognition at the same time to improve the recognition accuracy, the system uses the video as input, so that instantaneousness can not be achieved. In addition, this system has no evaluation on the confidence level of the face recognition and the speaker recognition, and misjudgments will occur easily in complicated environments.
Further, a human identification system as disclosed in U.S. Pat. Application No. 2005/0027530 uses a hidden Markov model (HMM) to fuse face recognition and speaker recognition. Although this system also integrates face recognition and speaker recognition and uses a special mechanism to improve the recognition accuracy, yet the system still has no evaluation on the confidence level of the face recognition and the speaker recognition, so that the system cannot function if any one of the recognitions is not operated normally.
In addition, most conventional human identification systems can only be applied at a fixed location, and they require a predetermined working environment, so that a too-large error will not occur during the recognition. However, if the working environment changes such as in an application of a service robot, the service robot is not set at a fixed location, but it moves around instead. Therefore, the working environment including the conditions of light and noise will be changed, and the conventional human identification systems may have misjudgments or failures on identifications.
Therefore, it is a main subject for the present invention to provide a human identification system not only featuring instantaneousness, but also improving the human recognition accuracy in a complicated varying environment.